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Past work on face detection has emphasized the issues of feature extraction and classification, however, less attention has been given on the critical issue of feature selection. We consider the problem of face and non-face classification from frontal facial images using feature selection and neural networks. We argue that feature selection is an important issue in face and non-face classification...
The aim of this paper is to develop efficient, robust and automated image frame fusion algorithms for mosaicing and super-resolution. Image registration is the key step in combining multiple independent low-resolution images to give one large mosaic image with high resolution. Our research is based on Scale Invariant Features Transform (SIFT detector/descriptor) for geometric and photometric images...
In this paper, we present a framework for 3D visual odometry applied to a hospital-use transfer robot equipped with an omni-drive system. The approach is based on features extracted out of and matched in monocular image sequences. We propose a new feature detection and tracking scheme robust to motion blur and well suitable in environment, as a hospital, where the local features are sparse and not...
This paper presents the face recognition using discrete orthogonal moment that is Krawtchouk moments (KMs) on combined features of global and local face images. KMs are considered due to their ability to localize face image according to region of interest (ROI) unlike other moments which generally capture the global features. To obtain the global face image, both parameters of KMs are set equal at...
This paper highlights the development of online signature verification system using support vector machine (SVM) and VBTablet 2.0 to verify the input signature by comparing database. This may take place by signing directly on to a digitizing tablet by using stylus which is connected to the universal serial bus (USB) port of computer. Owing to the fact that each individual has its own way of presenting...
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